Overview

Dataset statistics

Number of variables10
Number of observations385500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.4 MiB
Average record size in memory80.0 B

Variable types

Numeric10

Alerts

area[6] is highly overall correlated with area[8] and 1 other fieldsHigh correlation
area[8] is highly overall correlated with area[6] and 3 other fieldsHigh correlation
negpmax[8] is highly overall correlated with area[8] and 2 other fieldsHigh correlation
pmax[8] is highly overall correlated with area[6] and 3 other fieldsHigh correlation
pmax[9] is highly overall correlated with area[8] and 2 other fieldsHigh correlation
negpmax[8] is highly skewed (γ1 = -386.5507867)Skewed
negpmax[9] is highly skewed (γ1 = -280.3582782)Skewed

Reproduction

Analysis started2024-01-24 23:04:18.815447
Analysis finished2024-01-24 23:04:37.333374
Duration18.52 seconds
Software versionydata-profiling vv4.6.3
Download configurationconfig.json

Variables

area[6]
Real number (ℝ)

HIGH CORRELATION 

Distinct384022
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.2967059
Minimum-1.5756348
Maximum117.33014
Zeros0
Zeros (%)0.0%
Negative55
Negative (%)< 0.1%
Memory size2.9 MiB
2024-01-25T00:04:37.402403image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum-1.5756348
5-th percentile2.1700065
Q14.1330981
median6.7871356
Q310.984367
95-th percentile27.974449
Maximum117.33014
Range118.90577
Interquartile range (IQR)6.8512689

Descriptive statistics

Standard deviation8.2530964
Coefficient of variation (CV)0.88774416
Kurtosis6.3420305
Mean9.2967059
Median Absolute Deviation (MAD)3.0955841
Skewness2.3208371
Sum3583880.1
Variance68.113599
MonotonicityNot monotonic
2024-01-25T00:04:37.509567image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.179180908 3
 
< 0.1%
10.22197266 3
 
< 0.1%
7.401464844 3
 
< 0.1%
4.967797852 3
 
< 0.1%
6.911901855 3
 
< 0.1%
9.92364502 3
 
< 0.1%
4.470019531 3
 
< 0.1%
3.14850708 3
 
< 0.1%
3.788173828 3
 
< 0.1%
4.348803711 3
 
< 0.1%
Other values (384012) 385470
> 99.9%
ValueCountFrequency (%)
-1.575634766 1
< 0.1%
-0.5464337158 1
< 0.1%
-0.4896765137 1
< 0.1%
-0.4827404785 1
< 0.1%
-0.4823260498 1
< 0.1%
-0.4808154297 1
< 0.1%
-0.3892407227 1
< 0.1%
-0.3864587402 1
< 0.1%
-0.3785095215 1
< 0.1%
-0.375916748 1
< 0.1%
ValueCountFrequency (%)
117.3301367 1
< 0.1%
112.1752954 1
< 0.1%
99.39188843 1
< 0.1%
95.71105652 1
< 0.1%
95.07304749 1
< 0.1%
90.77695923 1
< 0.1%
86.7103717 1
< 0.1%
86.70578125 1
< 0.1%
85.57340698 1
< 0.1%
81.27600952 1
< 0.1%

tmax[6]
Real number (ℝ)

Distinct72127
Distinct (%)18.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78.3248
Minimum0
Maximum204.6
Zeros156
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:04:37.612375image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile35.931612
Q170.8
median71.4
Q372.0435
95-th percentile163.4
Maximum204.6
Range204.6
Interquartile range (IQR)1.2435005

Descriptive statistics

Standard deviation32.690131
Coefficient of variation (CV)0.41736629
Kurtosis4.4705267
Mean78.3248
Median Absolute Deviation (MAD)0.6
Skewness1.8049726
Sum30194210
Variance1068.6447
MonotonicityNot monotonic
2024-01-25T00:04:37.714353image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
71.4 25246
 
6.5%
71.8 24613
 
6.4%
71 24513
 
6.4%
70.6 23862
 
6.2%
71.2 23363
 
6.1%
70.8 23227
 
6.0%
71.6 23113
 
6.0%
72 22661
 
5.9%
72.2 17761
 
4.6%
70.4 15434
 
4.0%
Other values (72117) 161707
41.9%
ValueCountFrequency (%)
0 156
< 0.1%
0.2 1
 
< 0.1%
0.4 111
< 0.1%
0.6 161
< 0.1%
0.8 186
< 0.1%
1 191
< 0.1%
1.184952632 1
 
< 0.1%
1.2 215
0.1%
1.234949169 1
 
< 0.1%
1.237169547 1
 
< 0.1%
ValueCountFrequency (%)
204.6 173
< 0.1%
204.4 67
 
< 0.1%
204.2 51
 
< 0.1%
204 40
 
< 0.1%
203.8 53
 
< 0.1%
203.6 36
 
< 0.1%
203.4 30
 
< 0.1%
203.2 22
 
< 0.1%
203 35
 
< 0.1%
202.8615665 1
 
< 0.1%

rms[6]
Real number (ℝ)

Distinct385499
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3718027
Minimum0.31612721
Maximum5.4635651
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:04:37.811346image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0.31612721
5-th percentile0.83749125
Q11.1207464
median1.3475033
Q31.5965522
95-th percentile1.9892498
Maximum5.4635651
Range5.1474379
Interquartile range (IQR)0.47580573

Descriptive statistics

Standard deviation0.35200044
Coefficient of variation (CV)0.25659699
Kurtosis0.38685869
Mean1.3718027
Median Absolute Deviation (MAD)0.23683022
Skewness0.42651948
Sum528829.95
Variance0.12390431
MonotonicityNot monotonic
2024-01-25T00:04:37.909624image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.37587104 2
 
< 0.1%
1.699235715 1
 
< 0.1%
0.9671593747 1
 
< 0.1%
1.016034267 1
 
< 0.1%
1.210339633 1
 
< 0.1%
1.398157437 1
 
< 0.1%
0.7730649698 1
 
< 0.1%
1.266066888 1
 
< 0.1%
1.323793443 1
 
< 0.1%
1.665497149 1
 
< 0.1%
Other values (385489) 385489
> 99.9%
ValueCountFrequency (%)
0.3161272055 1
< 0.1%
0.3329717326 1
< 0.1%
0.3452157115 1
< 0.1%
0.3460045995 1
< 0.1%
0.3474135369 1
< 0.1%
0.3509861141 1
< 0.1%
0.3523480478 1
< 0.1%
0.3565417282 1
< 0.1%
0.3578788683 1
< 0.1%
0.3632073636 1
< 0.1%
ValueCountFrequency (%)
5.463565067 1
< 0.1%
4.990367338 1
< 0.1%
4.979964682 1
< 0.1%
4.858374174 1
< 0.1%
4.835121239 1
< 0.1%
4.610199707 1
< 0.1%
4.596534843 1
< 0.1%
4.527796777 1
< 0.1%
4.374894952 1
< 0.1%
4.327829518 1
< 0.1%

pmax[8]
Real number (ℝ)

HIGH CORRELATION 

Distinct380435
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.503279
Minimum1.4404026
Maximum128.18564
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:04:38.015012image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum1.4404026
5-th percentile4.2309779
Q16.4718452
median12.660268
Q325.45126
95-th percentile66.252813
Maximum128.18564
Range126.74523
Interquartile range (IQR)18.979414

Descriptive statistics

Standard deviation20.175681
Coefficient of variation (CV)0.98402218
Kurtosis2.982527
Mean20.503279
Median Absolute Deviation (MAD)7.1920425
Skewness1.8122612
Sum7904014
Variance407.05811
MonotonicityNot monotonic
2024-01-25T00:04:38.218323image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.78249817 3
 
< 0.1%
5.036624146 3
 
< 0.1%
16.4737854 3
 
< 0.1%
4.644863892 3
 
< 0.1%
6.10954895 3
 
< 0.1%
11.18064575 3
 
< 0.1%
6.300708008 3
 
< 0.1%
5.409152222 3
 
< 0.1%
4.347463989 3
 
< 0.1%
7.529141235 3
 
< 0.1%
Other values (380425) 385470
> 99.9%
ValueCountFrequency (%)
1.440402584 1
< 0.1%
1.998168945 1
< 0.1%
2.088098145 1
< 0.1%
2.149154663 1
< 0.1%
2.159881592 1
< 0.1%
2.160498047 1
< 0.1%
2.165744019 1
< 0.1%
2.168988037 1
< 0.1%
2.183538818 1
< 0.1%
2.196472168 1
< 0.1%
ValueCountFrequency (%)
128.1856354 1
< 0.1%
124.6846802 1
< 0.1%
124.2776459 1
< 0.1%
121.239679 1
< 0.1%
121.0509094 1
< 0.1%
120.6276978 1
< 0.1%
120.5172394 1
< 0.1%
120.1837646 1
< 0.1%
120.0050903 1
< 0.1%
119.9777771 1
< 0.1%

negpmax[8]
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct369406
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-12.218777
Minimum-86543.677
Maximum-0.010708011
Zeros0
Zeros (%)0.0%
Negative385500
Negative (%)100.0%
Memory size2.9 MiB
2024-01-25T00:04:38.320135image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum-86543.677
5-th percentile-40.228967
Q1-12.78878
median-5.8268799
Q3-4.7820323
95-th percentile-3.833358
Maximum-0.010708011
Range86543.666
Interquartile range (IQR)8.0067479

Descriptive statistics

Standard deviation184.96381
Coefficient of variation (CV)-15.13767
Kurtosis163433.14
Mean-12.218777
Median Absolute Deviation (MAD)1.5000909
Skewness-386.55079
Sum-4710338.5
Variance34211.61
MonotonicityNot monotonic
2024-01-25T00:04:38.415699image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-4.497241211 5
 
< 0.1%
-6.101940918 4
 
< 0.1%
-4.385882568 4
 
< 0.1%
-4.452893066 4
 
< 0.1%
-5.111987305 4
 
< 0.1%
-4.512332153 4
 
< 0.1%
-4.551531982 4
 
< 0.1%
-4.755514526 4
 
< 0.1%
-5.236392212 4
 
< 0.1%
-5.073501587 4
 
< 0.1%
Other values (369396) 385459
> 99.9%
ValueCountFrequency (%)
-86543.67718 1
< 0.1%
-64260.7395 1
< 0.1%
-24126.07168 1
< 0.1%
-21926.16077 1
< 0.1%
-14209.81894 1
< 0.1%
-12569.10799 1
< 0.1%
-6644.33526 1
< 0.1%
-3441.34874 1
< 0.1%
-3270.249332 1
< 0.1%
-3030.731684 1
< 0.1%
ValueCountFrequency (%)
-0.01070801087 1
< 0.1%
-0.7485331122 1
< 0.1%
-0.8274637895 1
< 0.1%
-1.043325005 1
< 0.1%
-1.287059168 1
< 0.1%
-1.287906776 1
< 0.1%
-1.422101743 1
< 0.1%
-1.460546422 1
< 0.1%
-1.502177266 1
< 0.1%
-1.613165303 1
< 0.1%

area[8]
Real number (ℝ)

HIGH CORRELATION 

Distinct384327
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.857352
Minimum-1.2421948
Maximum148.48612
Zeros0
Zeros (%)0.0%
Negative17
Negative (%)< 0.1%
Memory size2.9 MiB
2024-01-25T00:04:38.512272image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum-1.2421948
5-th percentile2.4346219
Q15.283902
median8.6222369
Q314.814062
95-th percentile33.153391
Maximum148.48612
Range149.72832
Interquartile range (IQR)9.5301596

Descriptive statistics

Standard deviation9.6335062
Coefficient of variation (CV)0.81245006
Kurtosis2.5821051
Mean11.857352
Median Absolute Deviation (MAD)4.1054114
Skewness1.6276649
Sum4571009.1
Variance92.804441
MonotonicityNot monotonic
2024-01-25T00:04:38.614132image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.983374023 3
 
< 0.1%
4.670336914 3
 
< 0.1%
6.709136963 3
 
< 0.1%
3.546582031 2
 
< 0.1%
9.440411377 2
 
< 0.1%
3.698666992 2
 
< 0.1%
13.99244141 2
 
< 0.1%
3.933770752 2
 
< 0.1%
10.56730652 2
 
< 0.1%
8.521959229 2
 
< 0.1%
Other values (384317) 385477
> 99.9%
ValueCountFrequency (%)
-1.242194824 1
< 0.1%
-0.4389428711 1
< 0.1%
-0.3881079102 1
< 0.1%
-0.35625 1
< 0.1%
-0.339465332 1
< 0.1%
-0.3325756836 1
< 0.1%
-0.3118798828 1
< 0.1%
-0.2431005859 1
< 0.1%
-0.2399414062 1
< 0.1%
-0.2209179688 1
< 0.1%
ValueCountFrequency (%)
148.486123 1
< 0.1%
113.9276703 1
< 0.1%
92.83317139 1
< 0.1%
85.30363525 1
< 0.1%
79.05072388 1
< 0.1%
78.59825928 1
< 0.1%
75.85489868 1
< 0.1%
74.18295898 1
< 0.1%
73.82571411 1
< 0.1%
72.75193848 1
< 0.1%

tmax[8]
Real number (ℝ)

Distinct59091
Distinct (%)15.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75.94907
Minimum0
Maximum204.6
Zeros103
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:04:38.721981image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile55.8
Q171.2
median71.8
Q372.4
95-th percentile137.2
Maximum204.6
Range204.6
Interquartile range (IQR)1.2

Descriptive statistics

Standard deviation26.31364
Coefficient of variation (CV)0.34646428
Kurtosis9.5852809
Mean75.94907
Median Absolute Deviation (MAD)0.6
Skewness2.461741
Sum29278366
Variance692.40765
MonotonicityNot monotonic
2024-01-25T00:04:38.818264image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
71.6 28356
 
7.4%
72 28331
 
7.3%
71.2 27893
 
7.2%
72.2 27518
 
7.1%
71.4 27117
 
7.0%
71.8 26743
 
6.9%
72.4 25882
 
6.7%
71 25875
 
6.7%
70.8 22202
 
5.8%
72.6 15954
 
4.1%
Other values (59081) 129629
33.6%
ValueCountFrequency (%)
0 103
< 0.1%
0.4 109
< 0.1%
0.6 127
< 0.1%
0.8 138
< 0.1%
1 114
< 0.1%
1.155305711 1
 
< 0.1%
1.164628011 1
 
< 0.1%
1.199000617 1
 
< 0.1%
1.2 106
< 0.1%
1.270006263 1
 
< 0.1%
ValueCountFrequency (%)
204.6 72
< 0.1%
204.4 28
 
< 0.1%
204.2 41
< 0.1%
204 38
< 0.1%
203.8 55
< 0.1%
203.6 18
 
< 0.1%
203.4 11
 
< 0.1%
203.2 20
 
< 0.1%
203 9
 
< 0.1%
202.8568181 1
 
< 0.1%

rms[8]
Real number (ℝ)

Distinct385499
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3899213
Minimum0.31975378
Maximum6.3900127
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:04:38.916912image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0.31975378
5-th percentile0.85344078
Q11.1382047
median1.3658855
Q31.6146682
95-th percentile2.0077106
Maximum6.3900127
Range6.0702589
Interquartile range (IQR)0.47646351

Descriptive statistics

Standard deviation0.35381426
Coefficient of variation (CV)0.25455704
Kurtosis1.010047
Mean1.3899213
Median Absolute Deviation (MAD)0.23733319
Skewness0.480163
Sum535814.67
Variance0.12518453
MonotonicityNot monotonic
2024-01-25T00:04:39.017689image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.119011794 2
 
< 0.1%
1.21146003 1
 
< 0.1%
1.807747432 1
 
< 0.1%
0.9992545641 1
 
< 0.1%
0.7419618396 1
 
< 0.1%
1.822619848 1
 
< 0.1%
1.268003483 1
 
< 0.1%
1.44229044 1
 
< 0.1%
1.078745266 1
 
< 0.1%
1.642961865 1
 
< 0.1%
Other values (385489) 385489
> 99.9%
ValueCountFrequency (%)
0.3197537765 1
< 0.1%
0.3286593493 1
< 0.1%
0.3414303649 1
< 0.1%
0.351511004 1
< 0.1%
0.3594876254 1
< 0.1%
0.3667699883 1
< 0.1%
0.3689140215 1
< 0.1%
0.3755076518 1
< 0.1%
0.3826756073 1
< 0.1%
0.3860786257 1
< 0.1%
ValueCountFrequency (%)
6.390012663 1
< 0.1%
5.956379542 1
< 0.1%
5.751987931 1
< 0.1%
5.495655267 1
< 0.1%
5.467067265 1
< 0.1%
5.423331086 1
< 0.1%
5.356367083 1
< 0.1%
5.293474315 1
< 0.1%
5.289633895 1
< 0.1%
5.273031071 1
< 0.1%

pmax[9]
Real number (ℝ)

HIGH CORRELATION 

Distinct374254
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.50553
Minimum1.7275299
Maximum115.56603
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:04:39.123858image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum1.7275299
5-th percentile3.8035393
Q14.9195282
median6.9962387
Q313.679469
95-th percentile44.634004
Maximum115.56603
Range113.8385
Interquartile range (IQR)8.7599403

Descriptive statistics

Standard deviation13.862611
Coefficient of variation (CV)1.1085184
Kurtosis9.3497389
Mean12.50553
Median Absolute Deviation (MAD)2.7276223
Skewness2.9052926
Sum4820881.8
Variance192.17197
MonotonicityNot monotonic
2024-01-25T00:04:39.236037image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.32807312 4
 
< 0.1%
5.070196533 4
 
< 0.1%
4.432476807 4
 
< 0.1%
3.656103516 4
 
< 0.1%
4.75062561 4
 
< 0.1%
14.24611816 4
 
< 0.1%
5.249139404 4
 
< 0.1%
4.651763916 4
 
< 0.1%
4.582171631 4
 
< 0.1%
4.285662842 4
 
< 0.1%
Other values (374244) 385460
> 99.9%
ValueCountFrequency (%)
1.727529907 1
< 0.1%
1.797338867 1
< 0.1%
1.85300293 1
< 0.1%
1.85480957 1
< 0.1%
1.897290039 1
< 0.1%
1.959057617 1
< 0.1%
1.968963623 1
< 0.1%
1.973324585 1
< 0.1%
1.975149536 1
< 0.1%
1.991933276 1
< 0.1%
ValueCountFrequency (%)
115.5660278 1
< 0.1%
113.1298523 1
< 0.1%
112.8514557 1
< 0.1%
112.7937439 1
< 0.1%
112.3648071 1
< 0.1%
112.253833 1
< 0.1%
111.3298248 1
< 0.1%
110.4649933 1
< 0.1%
109.9281006 1
< 0.1%
108.8988068 1
< 0.1%

negpmax[9]
Real number (ℝ)

SKEWED 

Distinct360906
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-8.1716424
Minimum-30718.927
Maximum-0.77151808
Zeros0
Zeros (%)0.0%
Negative385500
Negative (%)100.0%
Memory size2.9 MiB
2024-01-25T00:04:39.343908image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum-30718.927
5-th percentile-24.976307
Q1-6.4294009
median-5.1848832
Q3-4.470182
95-th percentile-3.6393396
Maximum-0.77151808
Range30718.156
Interquartile range (IQR)1.9592188

Descriptive statistics

Standard deviation73.012116
Coefficient of variation (CV)-8.9348153
Kurtosis97000.373
Mean-8.1716424
Median Absolute Deviation (MAD)0.85992902
Skewness-280.35828
Sum-3150168.1
Variance5330.7691
MonotonicityNot monotonic
2024-01-25T00:04:39.449545image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-4.588952637 5
 
< 0.1%
-5.66138916 5
 
< 0.1%
-4.148104858 5
 
< 0.1%
-4.680984497 5
 
< 0.1%
-4.750421143 5
 
< 0.1%
-4.766299438 5
 
< 0.1%
-4.691152954 5
 
< 0.1%
-4.523733521 5
 
< 0.1%
-4.663870239 5
 
< 0.1%
-4.404586792 5
 
< 0.1%
Other values (360896) 385450
> 99.9%
ValueCountFrequency (%)
-30718.92725 1
< 0.1%
-15758.64885 1
< 0.1%
-14758.02564 1
< 0.1%
-13676.73052 1
< 0.1%
-10705.44739 1
< 0.1%
-8128.541735 1
< 0.1%
-7902.857682 1
< 0.1%
-7508.544253 1
< 0.1%
-7499.832648 1
< 0.1%
-5910.141021 1
< 0.1%
ValueCountFrequency (%)
-0.7715180753 1
< 0.1%
-1.025246032 1
< 0.1%
-1.075532197 1
< 0.1%
-1.165804889 1
< 0.1%
-1.251938346 1
< 0.1%
-1.347146575 1
< 0.1%
-1.380709954 1
< 0.1%
-1.401534671 1
< 0.1%
-1.433758094 1
< 0.1%
-1.459381104 1
< 0.1%

Interactions

2024-01-25T00:04:35.558295image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:25.278127image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:26.376186image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:27.439005image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:28.505237image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:29.673243image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:30.912819image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:32.093215image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:33.226614image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:34.361099image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:35.669730image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:25.387344image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:26.480242image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:27.545307image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:28.615278image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:29.896041image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:31.033272image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:32.209945image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:33.346812image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:34.470614image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:35.778743image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:25.492425image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:26.581597image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:27.647455image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:28.733141image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:30.007954image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:31.149966image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:32.318380image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:33.455553image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:34.579667image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:35.882938image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:25.600711image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:26.686139image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:27.750881image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:28.849874image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:30.117312image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:31.267390image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:32.427860image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:33.567402image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:34.690569image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:35.993313image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:25.722319image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:26.797132image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:27.858972image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:28.962258image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:30.231651image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:31.384269image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:32.541667image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:33.685823image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:34.897351image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:36.100035image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:25.827036image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:26.901553image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:27.963949image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:29.079635image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:30.344058image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:31.501912image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:32.655093image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:33.799559image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:35.007073image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:36.210385image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:25.940717image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:27.011301image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:28.078198image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:29.199700image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:30.456060image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:31.620010image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:32.771557image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:33.915390image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:35.119991image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:36.315272image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:26.046214image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:27.115374image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:28.182599image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:29.315175image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:30.567888image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:31.740289image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:32.881226image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:34.017781image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:35.225638image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:36.424975image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:26.151773image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:27.221818image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:28.287277image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:29.432385image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:30.679951image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:31.856198image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:32.992081image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:34.126137image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:35.337560image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:36.536265image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:26.261803image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:27.325712image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:28.393656image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:29.555030image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:30.797681image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:31.974699image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:33.110701image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:34.249564image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:35.449991image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Correlations

2024-01-25T00:04:39.527209image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
area[6]area[8]negpmax[8]negpmax[9]pmax[8]pmax[9]rms[6]rms[8]tmax[6]tmax[8]
area[6]1.0000.515-0.4190.0020.5490.092-0.0040.000-0.149-0.122
area[8]0.5151.000-0.657-0.3880.9380.6530.000-0.001-0.127-0.198
negpmax[8]-0.419-0.6571.0000.421-0.732-0.5510.002-0.0040.1170.191
negpmax[9]0.002-0.3880.4211.000-0.412-0.4280.0020.0020.0180.098
pmax[8]0.5490.938-0.732-0.4121.0000.713-0.0000.001-0.138-0.214
pmax[9]0.0920.653-0.551-0.4280.7131.000-0.0000.001-0.029-0.155
rms[6]-0.0040.0000.0020.002-0.000-0.0001.000-0.002-0.020-0.006
rms[8]0.000-0.001-0.0040.0020.0010.001-0.0021.000-0.001-0.014
tmax[6]-0.149-0.1270.1170.018-0.138-0.029-0.020-0.0011.0000.426
tmax[8]-0.122-0.1980.1910.098-0.214-0.155-0.006-0.0140.4261.000

Missing values

2024-01-25T00:04:36.640866image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-25T00:04:36.856781image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

area[6]tmax[6]rms[6]pmax[8]negpmax[8]area[8]tmax[8]rms[8]pmax[9]negpmax[9]
02.07959728.4000001.24236126.581253-15.62553913.37425872.21.21146099.361264-56.828006
15.48152070.6000001.68481127.797015-11.74290214.33465771.01.24886996.062561-58.803436
26.07377771.5418591.52998123.163651-11.58195511.90132171.81.71270093.767398-62.801328
39.39318572.0815131.63316226.592899-10.40929912.23157072.20.82513189.620438-62.658493
44.21859470.7596821.79410925.261710-10.29804411.94975971.21.627493106.109430-68.653479
52.291220128.6000001.07448323.366986-12.84236512.65292071.01.307817101.398016-56.382227
65.942875165.4000001.82356628.292355-10.00244417.29861172.02.100437102.608847-64.914774
75.674915118.0000001.26643928.544223-13.74209313.85653472.21.96792199.802054-65.873636
81.796954147.0000000.86486824.306458-11.97052011.69768171.61.349982103.031000-67.912115
95.16488670.6000001.32105726.134976-12.74393011.49260670.80.69615293.711835-61.650256
area[6]tmax[6]rms[6]pmax[8]negpmax[8]area[8]tmax[8]rms[8]pmax[9]negpmax[9]
3854909.65572572.2000001.0070253.645273-5.1526402.52710070.2000001.6222724.973697-4.890378
3854913.316890171.0000001.2400755.482993-4.6897982.458395159.2000000.7123015.053085-5.502866
3854923.95485871.0570651.0921025.546344-4.6881533.74030093.0000001.2186554.427710-4.820825
3854932.94088170.8000001.3567763.986719-4.3217532.080461170.8000001.5557144.225861-6.580292
3854943.31158772.2000001.4743165.475406-5.8089573.132230169.0000001.2294276.182159-3.570309
3854953.77611789.2000001.5565234.668842-4.8073553.696760193.2000000.8762773.324582-4.966765
3854963.377163188.8000001.11239314.101810-4.98644711.56883372.2000001.94181512.819989-4.160602
3854973.60568171.0000001.0298417.160672-3.9445534.267343132.8000001.6121873.859982-5.145389
3854988.90260672.2000002.05027216.477707-4.3482186.24685172.1582321.79408711.385178-2.968319
3854993.87759971.6000001.7894874.402023-18.9135993.97290362.4000001.2074663.848242-20.433275